Overview

Brought to you by YData

Dataset statistics

Number of variables13
Number of observations14244
Missing cells2396
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory104.0 B

Variable types

DateTime1
Numeric12

Alerts

flow_avg is highly overall correlated with flow_max and 4 other fieldsHigh correlation
flow_max is highly overall correlated with flow_avg and 4 other fieldsHigh correlation
flow_min is highly overall correlated with flow_avg and 4 other fieldsHigh correlation
level_avg is highly overall correlated with flow_avg and 4 other fieldsHigh correlation
level_max is highly overall correlated with flow_avg and 4 other fieldsHigh correlation
level_min is highly overall correlated with flow_avg and 4 other fieldsHigh correlation
water_temp_avg is highly overall correlated with water_temp_max and 1 other fieldsHigh correlation
water_temp_max is highly overall correlated with water_temp_avg and 1 other fieldsHigh correlation
water_temp_min is highly overall correlated with water_temp_avg and 1 other fieldsHigh correlation
concent_solids has 230 (1.6%) missing valuesMissing
water_temp_avg has 722 (5.1%) missing valuesMissing
water_temp_max has 722 (5.1%) missing valuesMissing
water_temp_min has 722 (5.1%) missing valuesMissing
date has unique valuesUnique

Reproduction

Analysis started2025-02-20 14:57:51.795653
Analysis finished2025-02-20 14:57:58.468305
Duration6.67 seconds
Software versionydata-profiling vv4.9.0
Download configurationconfig.json

Variables

date
Date

UNIQUE 

Distinct14244
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size222.6 KiB
Minimum1985-01-01 00:00:00
Maximum2023-12-31 00:00:00
2025-02-20T15:57:58.573626image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-20T15:57:58.623321image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

flow_avg
Real number (ℝ)

HIGH CORRELATION 

Distinct1117
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.692099
Minimum9.06
Maximum926
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size222.6 KiB
2025-02-20T15:57:58.671128image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum9.06
5-th percentile20.4
Q131.8
median49.7
Q376.6
95-th percentile149
Maximum926
Range916.94
Interquartile range (IQR)44.8

Descriptive statistics

Standard deviation50.042658
Coefficient of variation (CV)0.7982291
Kurtosis33.459985
Mean62.692099
Median Absolute Deviation (MAD)20.6
Skewness4.0447695
Sum892986.26
Variance2504.2676
MonotonicityNot monotonic
2025-02-20T15:57:58.713001image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
104 48
 
0.3%
107 47
 
0.3%
101 43
 
0.3%
102 42
 
0.3%
28.6 41
 
0.3%
109 40
 
0.3%
106 39
 
0.3%
105 39
 
0.3%
26 38
 
0.3%
103 37
 
0.3%
Other values (1107) 13830
97.1%
ValueCountFrequency (%)
9.06 1
 
< 0.1%
10.5 1
 
< 0.1%
11.5 1
 
< 0.1%
11.7 1
 
< 0.1%
13 1
 
< 0.1%
13.3 1
 
< 0.1%
13.6 1
 
< 0.1%
13.7 1
 
< 0.1%
13.9 3
< 0.1%
14.1 1
 
< 0.1%
ValueCountFrequency (%)
926 1
< 0.1%
786 1
< 0.1%
767 1
< 0.1%
757 1
< 0.1%
747 1
< 0.1%
717 1
< 0.1%
707 1
< 0.1%
648 1
< 0.1%
568 1
< 0.1%
561 1
< 0.1%

flow_max
Real number (ℝ)

HIGH CORRELATION 

Distinct1156
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.704325
Minimum11.8
Maximum1050
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size222.6 KiB
2025-02-20T15:57:58.757037image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum11.8
5-th percentile23.1
Q138.6
median58.45
Q388.1
95-th percentile177
Maximum1050
Range1038.2
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation59.017005
Coefficient of variation (CV)0.80072648
Kurtosis29.528257
Mean73.704325
Median Absolute Deviation (MAD)23.15
Skewness3.9029255
Sum1049844.4
Variance3483.0068
MonotonicityNot monotonic
2025-02-20T15:57:58.800945image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
107 68
 
0.5%
103 64
 
0.4%
101 61
 
0.4%
102 60
 
0.4%
105 57
 
0.4%
111 54
 
0.4%
108 54
 
0.4%
106 53
 
0.4%
110 47
 
0.3%
104 46
 
0.3%
Other values (1146) 13680
96.0%
ValueCountFrequency (%)
11.8 1
 
< 0.1%
14.5 1
 
< 0.1%
14.7 2
 
< 0.1%
14.8 1
 
< 0.1%
14.9 1
 
< 0.1%
15 2
 
< 0.1%
15.1 5
< 0.1%
15.2 4
< 0.1%
15.3 4
< 0.1%
15.4 2
 
< 0.1%
ValueCountFrequency (%)
1050 1
< 0.1%
912 1
< 0.1%
830 1
< 0.1%
827 1
< 0.1%
814 1
< 0.1%
766 1
< 0.1%
761 1
< 0.1%
758 1
< 0.1%
715 1
< 0.1%
709 1
< 0.1%

flow_min
Real number (ℝ)

HIGH CORRELATION 

Distinct1102
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.726115
Minimum6.02
Maximum809
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size222.6 KiB
2025-02-20T15:57:58.845330image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum6.02
5-th percentile18
Q126.2
median40.7
Q365.4
95-th percentile124
Maximum809
Range802.98
Interquartile range (IQR)39.2

Descriptive statistics

Standard deviation42.688642
Coefficient of variation (CV)0.80962996
Kurtosis38.325011
Mean52.726115
Median Absolute Deviation (MAD)16.9
Skewness4.2311651
Sum751030.78
Variance1822.3202
MonotonicityNot monotonic
2025-02-20T15:57:58.889417image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23 68
 
0.5%
25 50
 
0.4%
23.6 50
 
0.4%
22.8 49
 
0.3%
24.3 49
 
0.3%
24.1 49
 
0.3%
24.8 46
 
0.3%
25.5 46
 
0.3%
21.2 45
 
0.3%
22.1 45
 
0.3%
Other values (1092) 13747
96.5%
ValueCountFrequency (%)
6.02 1
< 0.1%
6.49 1
< 0.1%
7.62 1
< 0.1%
7.66 1
< 0.1%
8.07 1
< 0.1%
8.65 1
< 0.1%
8.85 1
< 0.1%
8.9 1
< 0.1%
9.15 1
< 0.1%
9.23 1
< 0.1%
ValueCountFrequency (%)
809 1
< 0.1%
751 1
< 0.1%
733 1
< 0.1%
713 1
< 0.1%
649 1
< 0.1%
634 1
< 0.1%
521 1
< 0.1%
505 1
< 0.1%
502 1
< 0.1%
475 1
< 0.1%

level_avg
Real number (ℝ)

HIGH CORRELATION 

Distinct268
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.802373
Minimum19
Maximum495
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size222.6 KiB
2025-02-20T15:57:58.934346image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile42
Q160
median79
Q3100
95-th percentile149
Maximum495
Range476
Interquartile range (IQR)40

Descriptive statistics

Standard deviation35.857536
Coefficient of variation (CV)0.42283647
Kurtosis9.8565196
Mean84.802373
Median Absolute Deviation (MAD)20
Skewness2.0714917
Sum1207925
Variance1285.7629
MonotonicityNot monotonic
2025-02-20T15:57:58.979330image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59 214
 
1.5%
58 212
 
1.5%
75 211
 
1.5%
74 209
 
1.5%
72 208
 
1.5%
79 202
 
1.4%
55 202
 
1.4%
86 201
 
1.4%
54 197
 
1.4%
87 197
 
1.4%
Other values (258) 12191
85.6%
ValueCountFrequency (%)
19 1
 
< 0.1%
22 1
 
< 0.1%
24 1
 
< 0.1%
25 1
 
< 0.1%
27 9
0.1%
28 7
< 0.1%
29 11
0.1%
30 12
0.1%
31 7
< 0.1%
32 15
0.1%
ValueCountFrequency (%)
495 1
< 0.1%
450 1
< 0.1%
442 1
< 0.1%
432 1
< 0.1%
430 1
< 0.1%
414 2
< 0.1%
387 1
< 0.1%
352 1
< 0.1%
350 1
< 0.1%
343 1
< 0.1%

level_max
Real number (ℝ)

HIGH CORRELATION 

Distinct288
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.586633
Minimum25
Maximum542
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size222.6 KiB
2025-02-20T15:57:59.021777image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile48
Q168
median87
Q3108
95-th percentile165
Maximum542
Range517
Interquartile range (IQR)40

Descriptive statistics

Standard deviation39.50154
Coefficient of variation (CV)0.42208528
Kurtosis10.172091
Mean93.586633
Median Absolute Deviation (MAD)20
Skewness2.1956188
Sum1333048
Variance1560.3717
MonotonicityNot monotonic
2025-02-20T15:57:59.066159image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 228
 
1.6%
82 218
 
1.5%
91 215
 
1.5%
90 211
 
1.5%
88 206
 
1.4%
84 206
 
1.4%
87 205
 
1.4%
70 200
 
1.4%
85 199
 
1.4%
74 194
 
1.4%
Other values (278) 12162
85.4%
ValueCountFrequency (%)
25 1
 
< 0.1%
28 6
 
< 0.1%
29 3
 
< 0.1%
30 4
 
< 0.1%
31 9
 
0.1%
32 7
 
< 0.1%
33 17
0.1%
34 18
0.1%
35 26
0.2%
36 39
0.3%
ValueCountFrequency (%)
542 1
< 0.1%
491 1
< 0.1%
469 1
< 0.1%
467 1
< 0.1%
453 1
< 0.1%
439 1
< 0.1%
436 1
< 0.1%
432 1
< 0.1%
414 1
< 0.1%
411 1
< 0.1%

level_min
Real number (ℝ)

HIGH CORRELATION 

Distinct249
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.510601
Minimum11
Maximum451
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size222.6 KiB
2025-02-20T15:57:59.232187image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile37
Q153
median71
Q392
95-th percentile135
Maximum451
Range440
Interquartile range (IQR)39

Descriptive statistics

Standard deviation33.055575
Coefficient of variation (CV)0.43203915
Kurtosis9.2296606
Mean76.510601
Median Absolute Deviation (MAD)19
Skewness1.950734
Sum1089817
Variance1092.671
MonotonicityNot monotonic
2025-02-20T15:57:59.276523image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48 253
 
1.8%
52 244
 
1.7%
46 240
 
1.7%
51 234
 
1.6%
56 233
 
1.6%
47 233
 
1.6%
53 232
 
1.6%
54 226
 
1.6%
55 224
 
1.6%
49 217
 
1.5%
Other values (239) 11908
83.6%
ValueCountFrequency (%)
11 1
 
< 0.1%
13 1
 
< 0.1%
15 1
 
< 0.1%
16 1
 
< 0.1%
17 1
 
< 0.1%
19 3
< 0.1%
20 3
< 0.1%
21 1
 
< 0.1%
22 3
< 0.1%
23 7
< 0.1%
ValueCountFrequency (%)
451 1
< 0.1%
434 1
< 0.1%
425 1
< 0.1%
413 1
< 0.1%
389 1
< 0.1%
380 1
< 0.1%
334 1
< 0.1%
326 1
< 0.1%
324 1
< 0.1%
312 1
< 0.1%

concent_solids
Real number (ℝ)

MISSING 

Distinct3929
Distinct (%)28.0%
Missing230
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean18.621997
Minimum0.35
Maximum1292.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size222.6 KiB
2025-02-20T15:57:59.320104image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0.35
5-th percentile2.7165
Q16.7
median11
Q317.7575
95-th percentile51.2105
Maximum1292.14
Range1291.79
Interquartile range (IQR)11.0575

Descriptive statistics

Standard deviation39.882114
Coefficient of variation (CV)2.1416668
Kurtosis224.74159
Mean18.621997
Median Absolute Deviation (MAD)5.03
Skewness12.196003
Sum260968.67
Variance1590.583
MonotonicityNot monotonic
2025-02-20T15:57:59.366095image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 45
 
0.3%
4.44 25
 
0.2%
7 21
 
0.1%
12 21
 
0.1%
8.43 20
 
0.1%
7.05 20
 
0.1%
9.96 18
 
0.1%
4.82 18
 
0.1%
8 18
 
0.1%
11 18
 
0.1%
Other values (3919) 13790
96.8%
(Missing) 230
 
1.6%
ValueCountFrequency (%)
0.35 1
 
< 0.1%
0.42 1
 
< 0.1%
0.45 1
 
< 0.1%
0.46 4
< 0.1%
0.48 2
< 0.1%
0.49 3
< 0.1%
0.5 2
< 0.1%
0.51 1
 
< 0.1%
0.52 1
 
< 0.1%
0.53 3
< 0.1%
ValueCountFrequency (%)
1292.14 1
< 0.1%
992.69 1
< 0.1%
885.4 1
< 0.1%
862.21 1
< 0.1%
847.2 1
< 0.1%
755.56 1
< 0.1%
744.36 1
< 0.1%
713.79 1
< 0.1%
700.65 1
< 0.1%
693.32 1
< 0.1%

water_temp_avg
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct216
Distinct (%)1.6%
Missing722
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean9.967135
Minimum0.2
Maximum21.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size222.6 KiB
2025-02-20T15:57:59.411394image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile3.2
Q15.5
median9.7
Q314.2
95-th percentile17.7
Maximum21.8
Range21.6
Interquartile range (IQR)8.7

Descriptive statistics

Standard deviation4.859061
Coefficient of variation (CV)0.48750829
Kurtosis-1.1640994
Mean9.967135
Median Absolute Deviation (MAD)4.3
Skewness0.16769617
Sum134775.6
Variance23.610474
MonotonicityNot monotonic
2025-02-20T15:57:59.453890image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.2 205
 
1.4%
5 172
 
1.2%
4 157
 
1.1%
5.2 152
 
1.1%
4.4 149
 
1.0%
5.8 145
 
1.0%
4.6 145
 
1.0%
4.8 142
 
1.0%
6.2 137
 
1.0%
3.8 136
 
1.0%
Other values (206) 11982
84.1%
(Missing) 722
 
5.1%
ValueCountFrequency (%)
0.2 1
 
< 0.1%
0.3 3
 
< 0.1%
0.4 2
 
< 0.1%
0.6 1
 
< 0.1%
0.7 1
 
< 0.1%
0.8 6
< 0.1%
0.9 6
< 0.1%
1 10
0.1%
1.1 9
0.1%
1.2 11
0.1%
ValueCountFrequency (%)
21.8 1
 
< 0.1%
21.7 3
< 0.1%
21.6 1
 
< 0.1%
21.5 3
< 0.1%
21.4 3
< 0.1%
21.3 1
 
< 0.1%
21.2 6
< 0.1%
21.1 5
< 0.1%
21 4
< 0.1%
20.9 3
< 0.1%

water_temp_max
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct220
Distinct (%)1.6%
Missing722
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean10.278849
Minimum0.5
Maximum22.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size222.6 KiB
2025-02-20T15:57:59.498486image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile3.3
Q15.8
median10
Q314.5
95-th percentile18.3
Maximum22.4
Range21.9
Interquartile range (IQR)8.7

Descriptive statistics

Standard deviation4.9867413
Coefficient of variation (CV)0.48514587
Kurtosis-1.1379955
Mean10.278849
Median Absolute Deviation (MAD)4.3
Skewness0.18518921
Sum138990.6
Variance24.867589
MonotonicityNot monotonic
2025-02-20T15:57:59.542489image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.2 192
 
1.3%
5 170
 
1.2%
4.8 166
 
1.2%
5.2 161
 
1.1%
6 152
 
1.1%
4.4 149
 
1.0%
6.2 148
 
1.0%
5.8 147
 
1.0%
4.6 142
 
1.0%
4 141
 
1.0%
Other values (210) 11954
83.9%
(Missing) 722
 
5.1%
ValueCountFrequency (%)
0.5 3
 
< 0.1%
0.6 1
 
< 0.1%
0.7 1
 
< 0.1%
0.8 4
 
< 0.1%
0.9 1
 
< 0.1%
1 8
0.1%
1.1 6
< 0.1%
1.2 11
0.1%
1.3 4
 
< 0.1%
1.4 13
0.1%
ValueCountFrequency (%)
22.4 1
 
< 0.1%
22.3 2
 
< 0.1%
22.2 2
 
< 0.1%
22.1 2
 
< 0.1%
22 2
 
< 0.1%
21.9 2
 
< 0.1%
21.8 3
< 0.1%
21.7 4
< 0.1%
21.6 4
< 0.1%
21.5 6
< 0.1%

water_temp_min
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct213
Distinct (%)1.6%
Missing722
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean9.6619287
Minimum-0.1
Maximum21.4
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)< 0.1%
Memory size222.6 KiB
2025-02-20T15:57:59.669656image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum-0.1
5-th percentile3
Q15.3
median9.4
Q313.8
95-th percentile17.195
Maximum21.4
Range21.5
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation4.7583886
Coefficient of variation (CV)0.49248848
Kurtosis-1.166763
Mean9.6619287
Median Absolute Deviation (MAD)4.2
Skewness0.1635044
Sum130648.6
Variance22.642262
MonotonicityNot monotonic
2025-02-20T15:57:59.712496image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.2 213
 
1.5%
4 175
 
1.2%
5 169
 
1.2%
3.8 154
 
1.1%
4.8 151
 
1.1%
4.4 148
 
1.0%
14.8 146
 
1.0%
6 144
 
1.0%
5.2 140
 
1.0%
5.6 140
 
1.0%
Other values (203) 11942
83.8%
(Missing) 722
 
5.1%
ValueCountFrequency (%)
-0.1 2
 
< 0.1%
0.1 2
 
< 0.1%
0.2 3
< 0.1%
0.3 1
 
< 0.1%
0.4 2
 
< 0.1%
0.5 4
< 0.1%
0.6 5
< 0.1%
0.7 3
< 0.1%
0.8 6
< 0.1%
0.9 6
< 0.1%
ValueCountFrequency (%)
21.4 3
 
< 0.1%
21.2 6
< 0.1%
21.1 1
 
< 0.1%
21 4
< 0.1%
20.9 2
 
< 0.1%
20.8 2
 
< 0.1%
20.6 5
< 0.1%
20.5 4
< 0.1%
20.4 8
0.1%
20.3 3
 
< 0.1%

year
Real number (ℝ)

Distinct39
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2004
Minimum1985
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.9 KiB
2025-02-20T15:57:59.754715image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum1985
5-th percentile1986
Q11994
median2004
Q32014
95-th percentile2022
Maximum2023
Range38
Interquartile range (IQR)20

Descriptive statistics

Standard deviation11.254462
Coefficient of variation (CV)0.0056159992
Kurtosis-1.2015639
Mean2004
Median Absolute Deviation (MAD)10
Skewness0
Sum28544976
Variance126.66292
MonotonicityIncreasing
2025-02-20T15:57:59.796371image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
2004 366
 
2.6%
1992 366
 
2.6%
2012 366
 
2.6%
2000 366
 
2.6%
1996 366
 
2.6%
2016 366
 
2.6%
2020 366
 
2.6%
1988 366
 
2.6%
2008 366
 
2.6%
2019 365
 
2.6%
Other values (29) 10585
74.3%
ValueCountFrequency (%)
1985 365
2.6%
1986 365
2.6%
1987 365
2.6%
1988 366
2.6%
1989 365
2.6%
1990 365
2.6%
1991 365
2.6%
1992 366
2.6%
1993 365
2.6%
1994 365
2.6%
ValueCountFrequency (%)
2023 365
2.6%
2022 365
2.6%
2021 365
2.6%
2020 366
2.6%
2019 365
2.6%
2018 365
2.6%
2017 365
2.6%
2016 366
2.6%
2015 365
2.6%
2014 365
2.6%

month
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5231676
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.9 KiB
2025-02-20T15:57:59.834329image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4487589
Coefficient of variation (CV)0.52869389
Kurtosis-1.2079823
Mean6.5231676
Median Absolute Deviation (MAD)3
Skewness-0.0093842176
Sum92916
Variance11.893938
MonotonicityNot monotonic
2025-02-20T15:57:59.865799image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 1209
8.5%
3 1209
8.5%
5 1209
8.5%
7 1209
8.5%
8 1209
8.5%
10 1209
8.5%
12 1209
8.5%
4 1170
8.2%
6 1170
8.2%
9 1170
8.2%
Other values (2) 2271
15.9%
ValueCountFrequency (%)
1 1209
8.5%
2 1101
7.7%
3 1209
8.5%
4 1170
8.2%
5 1209
8.5%
6 1170
8.2%
7 1209
8.5%
8 1209
8.5%
9 1170
8.2%
10 1209
8.5%
ValueCountFrequency (%)
12 1209
8.5%
11 1170
8.2%
10 1209
8.5%
9 1170
8.2%
8 1209
8.5%
7 1209
8.5%
6 1170
8.2%
5 1209
8.5%
4 1170
8.2%
3 1209
8.5%

Interactions

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2025-02-20T15:57:57.773701image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Correlations

2025-02-20T15:57:59.900340image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
concent_solidsflow_avgflow_maxflow_minlevel_avglevel_maxlevel_minmonthwater_temp_avgwater_temp_maxwater_temp_minyear
concent_solids1.0000.4390.4570.4030.3250.3520.282-0.0520.1040.1040.105-0.185
flow_avg0.4391.0000.9840.9770.8990.9060.8490.0200.2820.2840.279-0.026
flow_max0.4570.9841.0000.9390.8670.9070.7970.0230.2910.2920.291-0.074
flow_min0.4030.9770.9391.0000.9010.8820.8930.0140.2650.2700.2610.027
level_avg0.3250.8990.8670.9011.0000.9810.9770.0220.2980.3040.2910.213
level_max0.3520.9060.9070.8820.9811.0000.9340.0270.3130.3160.3090.145
level_min0.2820.8490.7970.8930.9770.9341.0000.0150.2750.2840.2650.284
month-0.0520.0200.0230.0140.0220.0270.0151.0000.3460.3360.3560.000
water_temp_avg0.1040.2820.2910.2650.2980.3130.2750.3461.0000.9970.9970.073
water_temp_max0.1040.2840.2920.2700.3040.3160.2840.3360.9971.0000.9880.123
water_temp_min0.1050.2790.2910.2610.2910.3090.2650.3560.9970.9881.0000.019
year-0.185-0.026-0.0740.0270.2130.1450.2840.0000.0730.1230.0191.000

Missing values

2025-02-20T15:57:58.294856image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-02-20T15:57:58.362957image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-02-20T15:57:58.438012image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

dateflow_avgflow_maxflow_minlevel_avglevel_maxlevel_minconcent_solidswater_temp_avgwater_temp_maxwater_temp_minyearmonth
95581985-01-0118.019.916.838.041.036.05.313.83.83.819851
95591985-01-0217.121.315.537.043.034.05.282.52.52.519851
95601985-01-0324.132.420.647.057.042.05.542.42.42.419851
95611985-01-0423.529.818.646.054.039.06.982.32.32.319851
95621985-01-0523.736.820.646.062.042.08.542.12.12.119851
95631985-01-0620.724.316.242.047.035.010.111.81.81.819851
95641985-01-0719.727.316.240.051.035.011.681.11.11.119851
95651985-01-0831.742.619.956.068.041.013.251.21.21.219851
95661985-01-0939.550.633.365.076.058.014.821.21.21.219851
95671985-01-1036.847.526.662.073.050.016.041.11.11.119851
dateflow_avgflow_maxflow_minlevel_avglevel_maxlevel_minconcent_solidswater_temp_avgwater_temp_maxwater_temp_minyearmonth
237922023-12-22152.0193.0101.0169.0193.0138.011.695.86.05.6202312
237932023-12-23180.0186.0173.0185.0189.0182.012.215.85.95.6202312
237942023-12-24167.0179.0149.0178.0185.0168.011.055.96.25.7202312
237952023-12-25142.0149.0131.0163.0168.0157.010.356.46.66.2202312
237962023-12-26128.0133.0122.0155.0158.0151.09.995.96.45.7202312
237972023-12-27125.0128.0114.0153.0155.0146.09.725.96.05.5202312
237982023-12-28122.0130.0112.0151.0156.0145.09.565.35.65.1202312
237992023-12-29111.0115.0106.0144.0147.0141.09.465.76.05.4202312
238002023-12-30107.0114.091.9142.0146.0131.09.406.06.25.7202312
238012023-12-3182.690.079.5126.0131.0124.09.265.45.75.1202312